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Construction and Evaluation of Performance Measures for Bayesian Chain Sampling Plan (BChSP-1)

Listed author(s):
  • K. K., Suresh
  • K., Pradeepa Veerakumari
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    Bayesian Acceptance Sampling Approach is associated with utilization of prior process history for the selection of Distributions (viz., Gamma Poisson, Beta Binomial) to describe the random fluctuations involved in Acceptance Sampling. Calvin (1984) provides procedures and tables for implementing Bayesian Sampling Plan. Dodge (1955) has proposed Chain Sampling Plan in which Chain Sampling Plan allows significant reduction in sample size and the condition for a continuing succession of lots from a stable and trusted supplier. Usha (1991) has proposed procedure for Bayesian Chain Sampling Plan. Latha (2002) has further studied Bayesian Chain Sampling Plan – 1 involving designing of Bayesian Chain Sampling Plan indexed through AQL, LQL, OAOQL, and MAAPD. The main thrust of this paper is to account for the possibility of dependence among the items of a sample. This paper mainly relates with the procedure for designing Bayesian Chain Sampling Plan indexed with relative slopes at acceptable and limiting quality levels. Tables and Procedures are also provided for the selection of the parameters for the plan with specified h1, h0 and h2 (Relative Slopes). Numerical Illustration are also provided for the shop floor applications of these procedures.

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    Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 10105.

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    Date of creation: 2007
    Date of revision: 2007
    Publication status: Published in Acta Ciencia Indica 4.33(2007): pp. 16-35
    Handle: RePEc:pra:mprapa:10105
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